A study of clinical correlates and predictors of insight in obsessive compulsive disorder

Abstract

Background:

Obsessive compulsive disorder (OCD) is a clinically heterogeneous psychiatric disorder in terms of symptom content and insight.

Aim:

To study the various factors associated with insight in OCD.

Materials and Methods:

A cross-sectional hospital-based study was conducted among 40 patients with OCD who were evaluated on Yale-Brown Obsessive-Compulsive Scale, Hamilton Anxiety Rating Scale, Hamilton Depression Rating Scale, Brown Assessment of Beliefs Scale, Meta-Cognitions Questionnaire, WHOQOL-BREF, and Sheehan Disability Scale. Statistical analysis was done using SPSS version 22.

Results:

Metacognition, severity of OCD, and associated disability were the significant predictors for insight in patients with OCD.

Conclusion:

Factors associated with insight in OCD can enhance our understanding in the management of OCD.

INTRODUCTION

Obsessive compulsive disorder (OCD) is a common psychiatric disorder equally common in men and women having a chronic and disabling course.[1] The Epidemiological Catchment Area study reported a point prevalence of 1.3% and a lifetime prevalence of 2.5% in the general population.[2] It is a clinically heterogeneous condition in terms of both symptom content and insight into symptoms.[3]

Insight can be defined as a recognition of one’s emotional or mental problems or may even connote a sudden understanding of a problem based on various organizational strategies.[4] In OCD, insight into senselessness of symptoms is treated equivalent to insight into illness which may lie on a continuum of full awareness of senselessness or absurdity at one end to a total lack of any such awareness at the other end.[5] Insight is associated with other clinical variables such as severity, duration, age of onset of OCD, comorbid depression, anxiety, quality of life, disability, and intellect.[6,7,8] The relationship between insight as a clinical construct and other clinical characteristics is not well studied.[9,10]

Metacognition is the process of “thinking about thinking,” knowing about “what we know” and “what we don’t know”.[11,12] This metacognitive element is thought to be a major factor contributing to maladaptive response styles, which in turn favors the development and persistence of psychopathology. Patients with OCD are characterized by marked negative beliefs about worry, which is related to the severity of obsession, and show high need to control thoughts, as noticed by Moritz and his colleagues.[13] Only a few studies have investigated the impact of dysfunctional metacognition and its relationship with insight in OCD.[12,13] It is evident from the review that association between insight and factors associated is not well established, necessitating the need for research in this area.

MATERIALS AND METHODS

The cross-sectional study was conducted at a tertiary care psychiatric hospital at eastern India among 40 patients with OCD selected purposively according to the ICD-10 DCR (WHO, 1993) after being approved by the IEC. Inpatients or outpatients with OCD of both sexes between ages 18 and 50 years and an education level of class 5 and above giving informed written consent were included in the study. Patients with major physical disorder or any other major comorbid psychiatric diagnosis (except mild, moderate depression and anxiety) or substance dependence (except nicotine and caffeine) were excluded. The patients were rated on Yale-Brown Obsessive-Compulsive Scale (Y-BOCS), a clinician-rated 10-item scale, with additional item 11 for assessing insight, each item rated on a 5-point scale; Hamilton Anxiety Rating Scale (HAM-A), a clinician-rated 14-item test; Hamilton Rating Scale For Depression (HAM-D), a 21-item observer-rated scale to assess presence and severity of depressive states; Brown Assessment of Beliefs Scale (BABS), a seven-item clinician-administered semistructured scale designed to assess delusionality of beliefs developed to rate the degree of conviction and insight patients have concerning their beliefs; Meta-Cognitions Questionnaire-30 (MCQ-30), a 30-item self-report scale measuring beliefs about thinking applied to assess metacognitions; WHOQOL-BREF, the 26 items clinically rated 5-point rating scale divided into four domains, physical health, psychological, social relationships, and environmental; Sheehan Disability Scale (SDS), a 3-item self-report questionnaire that assesses the level of impairment experienced due to illness in social, occupational, and family life; and a semistructured sociodemographic and clinical data sheet.

Statistical analysis was done using Statistical Package for Social Sciences version 22. The two-tailed level of significance was kept at 0.05. Group differences for the continuous and categorical variables were computed using independent t-test and Chi-square test, respectively. Pearson’s correlation coefficients were computed between insight and other clinical variables. Finally, a step-by-step linear stepwise linear regression analysis was carried out to find the predictor variable for insight based on the predictor variables, that is, age of onset, education in years, duration of illness, OCD severity (YBOCS total score), severity of obsessions (YBOCS obsession score), severity of compulsion (YBOCS compulsion score), metacognition (MCQ-30 total score), quality of life (WHOQOL-BREF total score), disability (SDS total score), depression (HAM-D scores), and anxiety (HAM-A scores).

RESULTS

The sociodemographic and clinical characteristics revealed that the majority of the patients were married (n = 28), from a rural background (n = 28), aged 29.50 ± 7.46 years, and educated up to 11.88 ± 2.23 years. The mean age of onset was 23.10 ± 7.01 years with the mean duration of illness being 4.45 ± 3.21 years. The mean of insight score (BABS) was 10.85 ± 3.83. The mean YBOCS scores showed severe OCD, and mean anxiety (HAM-A) and depression (HAM-D) scores indicated mild depression and mild anxiety in the study sample [Table 1].

Table 1:

Sociodemographic and clinical characteristics of patients (n=40)

Variables	Mean+-SD/N (%)
Gender	Males n=21 (52.4%), Females n=19 (47.6%)
Marital Status	Married n=28 (70%), Unmarried n=12 (30%)
Mean age (years)	29.50±7.46
Age of onset (years)	23.10±7.01
Duration of Illness (years)	4.45±3.21
YBOCS Obsessions	15.48±1.24
YBOCS Compulsions	13.88±1.56
YBOCS Total	29.35±2.58
Insight (BABS)	10.85±3.83
Depression (HAM-D)	13.73±3.10
Anxiety (HAM-A)	14.78±4.55

Yale-Brown Obsessive-Compulsive Scale (Y-BOCS); Brown Assessment of Beliefs Scale (BABS); Hamilton Rating Scale For Depression (HAM-D)

The Pearson’s correlation test revealed that the insight scores had significant negative correlation with years of education (r = -.430 and P = .006), severity of OCD (r = -.602 and P = .001), severity of obsessions (r = -.562 and P < .001), severity of compulsions (r = -.549 and P < .001), and metacognition (r-.638 and P < .001) [Table 2]. There were no significant correlations of insight with age of onset, duration of illness, severity of depression, anxiety, quality of life, and disability among patients with OCD.

Table 2:

Correlation between scores obtained on insight and clinical characteristics among the patients with OCD (n=40)

Variables	r	P
Education in years	-0.430	0.006**
YBOCS (TOTAL SCORE)	-0.602	<0.001***
YBOCS (Obsession SCORE)	-0.562	<0.001***
YBOCS (Compulsion SCORE)	-0.549	<0.001***
MCQ-30 SCORE	-0.638	<0.001***

*P<0.05; **P<0.01; ***P<0.001. Yale-Brown Obsessive-Compulsive Scale (Y-BOCS); Meta-Cognitions Questionnaire-30 (MCQ-30)

Metacognition, severity of OCD, and associated disability were the significant predictors for insight in OCD patients. Metacognition, severity of OCD, and associated disability could explain 52.4% of variability in predicting insight in patients with OCD [Table 3].

Table 3:

Predictor variables for insight in patients with OCD (n=40)

Predictors	R	R2	Adjusted R2	R2 change	P
Metacognition	0.638	0.407	0.392	0.407	<.001***
Metacognition + Severity of OCD	0.711	0.505	0.478	0.098	0.010*
Metacognition + Severity of OCD + Disability	0.748	0.560	0.524	0.055	0.040*

*P<0.05; **P<0.01; ***P<0.001

DISCUSSION

The study subjects were recruited using purposive sampling, and the sample had almost equal representation of both genders, with more than half married from middle socioeconomic strata and the average education level of higher secondary, which is consistent with the sample characteristics of other researches done previously.[6,7,9,14] Insight is an issue of concern in OCD, and so are the various factors associated with insight in OCD like age of onset, duration of illness, severity of OCD, education, depression, anxiety, and disability. The “with poor insight” specifier for OCD has been refined in DSM-5 to allow a distinction between individuals with good or fair insight, poor insight, and “absent insight/delusional” beliefs, which means complete conviction that OCD beliefs are true. These specifiers aim to improve differential diagnosis of the OCD spectrum by showing that individuals with these disorders may present with a range of insight into their disorder-related beliefs, including absent insight or delusional symptoms, which warrants a diagnosis of the relevant obsessive-compulsive or related disorder, rather than a schizophrenia spectrum disorder, because this may have relevant clinical implications and henceforth has led to refinement of insight in OCD to good or fair insight, poor insight, and absent insight/delusional OCD beliefs in DSM-5.[15]

Studying clinical correlates of insight has important clinical implications. Insight is a consistently recognized prognostic indicator, particularly indicative of poor response to treatment.[14,16,17] Moreover, studies have examined insight in OCD as a dichotomous entity (good vs poor) instead of treating insight as a continuous variable.[14,18] Hence, the present study was carried out with the intent of systematically examining insight and its relationship with specific clinical characteristics. As insight varies from total awareness to denial of illness, Brown assessment of beliefs scale (BABS) used in our study is a more valid and reliable measure of insight in OCD as it taps the dimensional nature of insight more effectively.[19] Insight connotes an understanding of a problem based on various organizational strategies, but it is somewhat vague. It is a very complex construct that is multidimensional and influenced by many internal and external factors.[4] This study is a comprehensive study investigating almost all possible factors related to insight.

In this study, we found no significant correlation of insight with age of onset, income status, duration of illness, severity of depression, severity of anxiety, quality of life, and disability in OCD patients. In previous studies, poor insight has been associated with the presence of depression and anxiety.[9,14] Also, some studies have found that patients with more severe depression and more severe anxiety symptoms had a lower level of insight concerning the obsessive compulsive symptoms.[6,7] Other studies suggest that diminished insight is related to longer duration of illness and early onset of symptoms. Moreover, poorer insight has been correlated with poorer quality of life and more disability.[17] In another recent study on correlates of insight among patients with OCD,[18] a computerized search of the literature published from 1966 to July 2013 was conducted on Medline and Web of Science using words “obsessive compulsive disorder” and “insight” and results showed poor insight was associated with more severe disorder, longer duration of illness, early onset of symptoms, chronic course, family history of OCD, and comorbid diagnoses. Poor insight patients had increased risk of comorbid symptoms, worse adaptive functioning, and treatment outcomes. We failed to find any such correlations, and this is supported by two previous studies which also failed to find any such correlations.[7,20]

The insight scores of OCD patients on BABS in our study had significant negative correlation with years of education, severity of obsessions, severity of compulsions, severity of OCD, and metacognition. This meant that better insight was seen with more education, more severe obsessions, compulsions, and overall disorder (OCD) severity and higher metacognitions. The findings in this study are different from few of the prior studies done in this area, which could be due to the small sample size and the sample taken from a tertiary care hospital. Also, we found that metacognition, severity of OCD, and associated disability were the significant predictors for insight in OCD patients. Metacognition, severity of OCD, and associated disability could explain 52.4% of variability in predicting insight in OCD patients. The other variabilities as predictors of insight could be duration of illness, years of education, treatment duration, and treatment modalities for which future studies taking a larger sample from community and a prospective study design could be hugely beneficial.

Literature on the clinical correlates of insight in OCD from the Indian population is sparse. The varied findings from different studies across the globe on this and more so very few studies done from our part of the world highlight the need for further studies on this important aspect. Factors associated with insight in OCD are important aspects worth paying attention as they may help in proper assessment and management plan for better outcome of this common psychiatric disorder.

LIMITATIONS OF THE STUDY

The cross-sectional nature of the study was one of the major limitations. The sample size calculations were not done, but they are based on a modest sample size, considering the comprehensive assessment in a limited time span. The issue of ego syntonicity–dystonicity of symptoms of OCD in relevance to insight could not be analyzed, and the role of metacognitions, comorbid depression, anxiety, disability, quality of life, symptom dimensions associated with course, and outcome of OCD was not investigated.

CONCLUSION

This study shows better insight is associated with better education level, severe illness, and higher metacognitions. Also, metacognition, severity of OCD, and associated disability together are the best predictors for insight in OCD patients. Future studies are needed on larger populations drawn from community samples with a prospective design.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.